Pivotal Inference for the Inverted Exponentiated Rayleigh Distribution Based on Progressive Type-II Censored Data

Abstract

In this article, the pivotal inference is proposed to estimate the two unknown parameters of the inverse exponentiated Rayleigh distribution based on progressive censored data. We derive the point estimator and construct an interval estimator using the pivotal quantity method. To compare the performance of this proposed method and the traditional maximum likelihood estimation method, a simulation study is conducted. The simulation results show that the proposed method performs better in terms of bias and mean squared error. Finally, a real dataset is used to illustrate the proposed approaches.

KEYWORDS AND PHRASES:

• Inverted exponentiated Rayleigh distribution
• maximum likelihood estimation
• Monte Carlo simulation
• pivotal quantity
• progressive type-II censoring

Acknowledgements

The authors would like to thank the editor and anonymous referees for their constructive comments and suggestions that have substantially improved the original manuscript.

Additional information

Funding

Jiao Yu’s work was supported by Project 201910004093 which was supported by National Training Program of Innovation and Entrepreneurship for Undergraduates. Wenhao Gui’s work was partially supported by the National Statistical Science Research Project of China (No. 2019LZ32).